Neurology

Head Trauma

Latest AI and machine learning research in head trauma for healthcare professionals.

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Machine learning models for predicting early hemorrhage progression in traumatic brain injury.

This study explores the progression of intracerebral hemorrhage (ICH) in patients with mild to moder...

Oral ketamine effects on dynamics of functional network connectivity in patients treated for chronic suicidality.

The underlying brain mechanisms of ketamine in treating chronic suicidality and the characteristics ...

Brain Deformation Estimation With Transfer Learning for Head Impact Datasets Across Impact Types.

OBJECTIVE: The machine-learning head model (MLHM) to accelerate the calculation of brain strain and ...

A complex fuzzy decision model for analysing the post-pandemic immuno-sustainability.

The post-effects of the COronaVIrus Disease (COVID-19) vary depending on socioeconomic and biologica...

Usefulness of Artificial Intelligence in Traumatic Brain Injury: A Bibliometric Analysis and Mini-review.

BACKGROUND: Traumatic brain injury (TBI) has become a major source of disability worldwide, increasi...

Employing machine learning for enhanced abdominal fat prediction in cavitation post-treatment.

This study investigates the application of cavitation in non-invasive abdominal fat reduction and bo...

The Impact of Drop Test Conditions on Brain Strain Location and Severity: A Novel Approach Using a Deep Learning Model.

In contact sports such as rugby, players are at risk of sustaining traumatic brain injuries (TBI) du...

Using machine learning to discover traumatic brain injury patient phenotypes: national concussion surveillance system Pilot.

OBJECTIVE: The objective is to determine whether unsupervised machine learning identifies traumatic ...

Predicting osteoporotic fractures post-vertebroplasty: a machine learning approach with a web-based calculator.

PURPOSE: The aim of this study was to develop and validate a machine learning (ML) model for predict...

Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle.

This study aimed to compare the accuracy of IFN-Ï„ stimulated gene abundance (ISGs) in peripheral blo...

Closing the loop in minimally supervised human-robot interaction: formative and summative feedback.

Human instructors fluidly communicate with hand gestures, head and body movements, and facial expres...

Using machine learning to increase access to and engagement with trauma-focused interventions for posttraumatic stress disorder.

BACKGROUND: Post-traumatic stress disorder (PTSD) poses a global public health challenge. Evidence-b...

GNN-based structural information to improve DNN-based basal ganglia segmentation in children following early brain lesion.

Analyzing the basal ganglia following an early brain lesion is crucial due to their noteworthy role ...

mRNA-CLA: An interpretable deep learning approach for predicting mRNA subcellular localization.

Messenger RNA (mRNA) is vital for post-transcriptional gene regulation, acting as the direct templat...

Machine learning for predicting elective fertility preservation outcomes.

This retrospective study applied machine-learning models to predict treatment outcomes of women unde...

Exploring post-COVID-19 health effects and features with advanced machine learning techniques.

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a rang...

Protocol to identify biomarkers in patients with post-COVID condition using multi-omics and machine learning analysis of human plasma.

Here, we present a workflow for analyzing multi-omics data of plasma samples in patients with post-C...

Artificial Intelligence for Quantifying Cumulative Small Bowel Disease Severity on CT-Enterography in Crohn's Disease.

INTRODUCTION: Assessing the cumulative degree of bowel injury in ileal Crohn's disease (CD) is diffi...

Detecting white spot lesions on post-orthodontic oral photographs using deep learning based on the YOLOv5x algorithm: a pilot study.

BACKGROUND: Deep learning model trained on a large image dataset, can be used to detect and discrimi...

The gut microbiome associates with phenotypic manifestations of post-acute COVID-19 syndrome.

The mechanisms underlying the many phenotypic manifestations of post-acute COVID-19 syndrome (PACS) ...

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